analytic challenges to valuing energy storage · sixteen stakeholders and experts from across the...

Office of Energy Efficiency and Renewable Energy

Office of Electricity Delivery and Energy Reliability

Analytic Challenges to Valuing Energy

Storage

WORKSHOP REPORT

NOVEMBER 2011

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Notice: This report was prepared as an account of work sponsored by an agency of the United States

government. Neither the United States government nor any agency thereof, nor any of their employees,

makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy,

completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents

that its use would not infringe privately owned rights. Reference herein to any specific commercial product,

process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute

or imply its endorsement, recommendation, or favoring by the United States government or any agency

thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the

United States government or any agency thereof.

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About this Report This report was drafted by the Department of Energy under the support of Henry Kelly, Mike Davis, and

Carla Frisch in the Office of Energy Efficiency and Renewable Energy and under the support of Pat

Hoffman, Bill Parks, and Imre Gyuk in the Office of Electricity Delivery and Energy Reliability. Principal

authors were Ookie Ma (EERE), Mark O’Malley (UCD), Kerry Cheung (AAAS, OE), and Philippe Larochelle

(ORISE, ARPA-e) with contributions from Rich Scheer (Scheer Ventures). Editing services were provided

by Bruce Green (NREL). We thank the participants and acknowledge Peter Wong, David Bertagnolli, and

Wayne Coste of ISO New England for providing additional comments.

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Contents About this Report .......................................................................................................................................... ii

Introduction and Process .............................................................................................................................. 1

Key Takeaways .............................................................................................................................................. 1

Analysis Areas ............................................................................................................................................... 1

Scenarios and Drivers ............................................................................................................................ 1

Power System Requirements ................................................................................................................ 3

Electricity Markets ................................................................................................................................ 3

Valuation Methods ............................................................................................................................... 5

Economics ............................................................................................................................................. 7

Appendix ....................................................................................................................................................... 8

Participants ............................................................................................................................................... 8

Invited Experts ...................................................................................................................................... 8

Department of Energy Observers ......................................................................................................... 8

Planning Team ....................................................................................................................................... 8

Initial Questions ........................................................................................................................................ 9

Group Discussion Template .................................................................................................................... 10

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Introduction and Process The U.S. Department of Energy (DOE) has coordinated energy storage efforts across the Office of

Electricity Delivery and Energy Reliability (OE), the Office of Energy Efficiency and Renewable Energy

(EERE), the Office of Science Basic Energy Sciences (BES), and the Advanced Research Projects Agency-

Energy (ARPA-e) from a research and development (R&D) perspective – identifying technology needs,

metrics, and goals – but DOE and the research and analytic community have struggled with valuing

storage at a systems level.

Sixteen stakeholders and experts from across the electric power industry, research universities, national

laboratories, and federal agencies were invited to join 8 DOE staff members in a workshop on

September 19-20, 2011, in Washington, D.C. to discuss the current state of knowledge for grid-scale

energy storage and, in particular, the methodologies to assess its value on the grid. Storage

technologies are continually evolving in terms of both cost and performance; and thus, the discussion

focused on the functionalities of storage as a system-level asset for the grid rather than on individual

storage technologies. The discussions were designed to generate a diversity of opinions and

perspectives on analysis directions and priorities. However, having comprehensive coverage of

stakeholders’ opinions and achieving consensus were not goals of the workshop.

The scope of the workshop covered mechanical and electrochemical means of storing electricity including,

for example, batteries, flywheels, compressed air, and pumped hydroelectric systems in grid-connected

applications including frequency regulation, peak load reduction, arbitrage, distributed energy, and volt/VAr

control. While energy storage systems can provide multiple services in electricity markets, there are

competing technologies, tools, and techniques that also provide these same services. A key goal was to

identify the most important analysis questions to answer about energy storage in light of competing

technologies and multiple applications so that policy and decision makers can more fully assess the technical

and economic potential for grid-connected energy storage as a resource for power system planning,

operations, and customer-side solutions.

The workshop involved a series of discussions from a select group of individuals aimed at informing DOE

about the state of the art in the analysis of grid-scale energy storage, including the relative merits of

existing methods, models, computational tools, and data sources.

Key Takeaways Flexibility − Energy storage can provide flexibility to the grid, both in operations and in planning, and

adding variable renewable generation such as wind and solar onto the grid increases that need for

flexibility. However, energy storage is generally not the only solution to challenges on the grid, and it

competes with other options like dispatchable generation, upgrades to infrastructure, improved

forecasting, better market designs, and demand response. Deployment of energy storage can yield

efficiency gains through improved generator dispatch, more efficient generator operating points, and

higher utilization of grid assets; but overall system-level gains are limited by the round-trip efficiency

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and capital cost of energy storage devices. Thus, determination of multiple price points at which energy

storage technologies become the cost effective solutions is both a rich field of study and a challenging

analytical task.

Market Conditions − Markets are continually evolving, and the long-term value of energy storage is

difficult to capture. Niche markets have emerged, but storage still lacks a unique value proposition with

a large opportunity base. Niche areas include frequency regulation in wholesale markets, stability for

remote or island systems and weakly coupled sections of the grid, and, under specific circumstances,

infrastructure investment deferral at both transmission and distribution levels. Other opportunities

exist, but their economics depend on the compatibility of multiple applications for shared storage

capacity, both in terms of revenue recovery through markets and regulatory structures (less transaction

costs), and in terms of technical and operational feasibility. Wider market opportunities may emerge as

storage technologies decline in cost on a power ($/kW) and energy ($/kWh) basis. The value of

distributed storage to the bulk power system, and the value that can be monetized, is relatively

unexplored and further research may lead to identification of additional benefits.

Drivers and Synergies −The question remains to what extent increasing levels of variable renewable

energy (RE) serve as a driver for deployment of energy storage. Integration of variable renewable

generation is one of many aspects of the future grid that will have an impact on the value of storage. In

moving forward, there are several potential synergies with renewable generation. Storage can capture

intermittent renewable energy that would have been curtailed due to transmission constraints or over-

generation; and current expectations are the addition of variable renewables will make more storage in

the bulk power system attractive at high renewable energy penetration levels. This level is possibly in

excess of 30-40% by energy, unless there are dramatic reductions in the capital costs and/or

improvements in performance of energy storage. It is worth noting, that the economics of combining

variable renewable plants with dedicated energy storage tend to be sub-optimal, since the value of the

curtailed energy plus the avoided cost of incremental transmission capacity is typically not sufficient to

cover storage costs and the lost opportunity of providing other grid services. Storage can provide

flexibility to help manage variability from the large deployment of wind and/or solar PV and generally,

has greater value if deployed as a system-level asset to the grid rather than one dedicated to individual

wind or solar plants. Lastly, as renewables displace energy provided by dispatchable generation,

capacity market prices may increase. Capacity value is also one of the many possible value streams for

storage, and is necessary for utility resource planning. Determining the capacity value of energy

storage technologies is a difficult research question to address, particularly for energy-limited devices,

as it involves modeling detailed system operations and representing other value streams over a long

time horizon.

Barriers − There are substantial challenges to incorporating energy storage into long-term utility

planning. As an investment, energy storage currently struggles with demonstrating economic returns

sufficiently high to justify a number of risks. Regulatory issues at the federal and state level may limit

the value proposition for energy storage and removing them may be necessary to level the playing field

with other technologies. Aside from the long history with operating pumped hydropower storage

plants, most storage technologies do not have standard and proven characterizations, though the

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Recovery Act-funded demonstration projects will provide valuable application data. Overall, the value

of storage is highly system-dependent, location-dependent, and subject to risk and uncertainty;

technical, regulatory, and financial. Given the complex nature of energy storage, straightforward and

transparent analysis is critical to build impact with stakeholders and give functional information to

decision makers.

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SUMMARY OF ANALYSIS AREAS AND QUESTIONS (number of votes in bold)

Drivers and Scenarios How will technologies,

markets, and policies affect energy storage deployments (e.g., gas prices, RPS, demand response)? (8)

What is the optimum mix of solar, wind, and storage to produce the maximum production of renewable energy on peak? (2)

To what extent can energy storage facilitate a large scale expansion of renewable energy in a cost effective manner?

What are the likely “end points” of the electric infrastructure in the 202-2050 time frame?

How much does the U.S. need to invest to have a viable domestic energy storage industry?

Power System Requirements How should energy storage be

integrated into long-term planning processes including what storage evaluation methods in standard reliability tools like PSLF and PSS/E can be used to fully model storage for transmission? (11)

What level of solar penetration (%) on a distribution circuit causes uncertain voltage control? (3)

What interconnection requirements are needed for storage? (3)

What are the requirements for maximizing the benefits of distributed storage to the bulk power system? (3)

What kind of grid is desired in terms of organizational structure and extent of central vs. distributed? (1)

Are the impacts of changes in frequency on the integrity of generators fully known (in terms of $ and the ability to extract energy from the rotating moment of inertia? (1)

What are the needs for frequency response including primary frequency response? (1)

What are the system characteristics that drive the needs for storage?

Valuation Methods What algorithms or

methodologies can be used to seamlessly aggregate several of the benefits of energy storage? (10)

What is the value of distributed storage, including: locational values; converting impacts, to benefits, to values; for reliability, load smoothing, and integration of renewables? (6)

What is the capacity credit to give storage for resource adequacy? (5)

What is the state-of-the-art of existing analysis about the value of storage? (3)

What is the set of cost effective analysis tools for valuing storage? (1)

How to quantify the value of storage in reducing volatility? (1)

Can energy storage be input into engineering software tools to evaluate the effectiveness of that investment?

Can energy storage provide multiple services and serve multiple roles from a single facility?

What are the benefits of faster response to regulation signals?

How can storage be integrated into an operation paradigm for arbitrage and regulation (stacked)?

Economics How does the value of

storage change depending on the capabilities (e.g., # of hours, ramp rate, and depth of discharge)? (7)

What is the market for storage as a function of cost? (4)

How does the value of storage vary as a function of the penetration of variable renewable generation? (1)

Where does energy storage fit on the flexibility supply curve for integrating variable renewable generation? (1)

What is the total installed cost of storage now and three years from now?

What will it cost to operate the electric system if no new storage is built?

Electricity Markets What market structures

are needed to support the energy storage business case and do existing mechanisms adequately compensate storage for all of the benefits for integrating variable renewable generation? (6)

Are current regulatory and market mechanisms adequate for energy storage? (1)

Is the value of energy storage enhanced if control of the facility is turned over to an RTO/ISO?

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Analysis Areas The remainder of this document summarizes several key questions that were identified by the workshop

participants. The questions are categorized in the table above. The workshop participants were asked

to identify the key questions that they felt were most important to answer in order to better understand

the value of storage. The participants then formed groups to create a research project that could

answer these questions. The summaries of the resulting research projects in each of the Analysis Areas

are presented below.

Scenarios and Drivers Analyzing the value and/or impact of any grid scale technology in the context of the future

developments is important, particularly for those that impact the grid itself. This is a difficult task

because the future is far from certain. Examples of the types of changes that may impact the value of

SCENARIOS AND DRIVERS Analysis/ Research Question

How will storage deployment be impacted by the following scenarios & drivers?

Low-cost PV

High penetration of variable renewables

Low storage costs

Fossil fuel prices

Demand response and efficiency increase

Low and high transmission build outs

Low growth and high growth

Policy scenarios

Financial collapse

Climate change

Market structures

Preferred Methodologies

and Tools

Tools and methods should factor in:

Path dependency (evolution)

Multi-agent aspects

Multiple time horizons

Supercomputing needs

Capturing multiple values

Production cost simulation

Representation of smart grid

Population shifts and locations

Borrow from other domains like National Energy Modeling System (NEMS)

Data Needs and Gaps

20 years of 1-minute resolution for renewable generation (wind and solar)

Loads aggregated and not distributed

Storage life cycle and trigger points

Risks, Limitations, and Caveats

Simplifying for computational reasons can miss important elements

Lack of data at extremes leads to very large errors

Level of uncertainty may be so ill defined as to lead to meaningless results

Time to do the story and the time of the story horizon

Credibility and the sources of the data

Level-of-Effort $10 − $20 million per year

Key Features to Make the

Analysis Used and Useful to Policy

and Decision Makers

Ability to re-run and repeatability of results

Open source

Simple distribution

Community of researchers

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storage include: high gas prices, renewable portfolio standards, and developments in demand side

response, etc. Questions pertaining to these various scenarios include what is the optimal mix of

renewable energy sources and storage in the future grid. Answering these questions presents a very

high dimensional problem-domain with a vast number of possible outcomes, is path dependent, and

very sensitive to initial conditions. Substantial computational resources may be required in addition to

borrowing from methodologies from other disciplines, and all approaches will require extensive and

detailed datasets (which currently may not exist). Finding robust results within all the uncertainty is a

very difficult task and any approach will necessarily have to be probabilistic, require very detailed

models, and are computationally very challenging. Furthermore, the quality of the answers for any

analysis conducted with existing capabilities is unlikely to be sufficiently robust considering the

complexity of the problem, the lack of high-quality data, etc.

POWER SYSTEM REQUIREMENTS, Part 1 Analysis/Research

Question How can storage be integrated into long-term planning?

How do we know when storage can displace transmission in the queue? How does this coordinate with stochastic transmission planning and operations?

How do we integrate it? How do we operate it?

How do we compute system reliability? Should we really use N-1 contingency analysis? Or maybe a more complex assessment?

Development of software

(N-1 or some) contingency analysis

Standardized storage types

Development of storage dispatch algorithms

Including storage in GTO long- term plan

PROMOD, UPLAN, WASP, etc.

Preferred Methodologies and

Tools

New tool or new module within an existing tool

Physical model of voltage, amps, power

Economics (costs of operating compared to others)

Automatic generation control (AGC) for storage devices (comparison within storage and with other assets)

Dispatch and control strategies

LMP calculations need to be modified to include storage

Model 17 benefits of storage, but model has to be able to optimize based on user needs (practicality says 2 − 3 of the 17 benefits)

Data Needs and Gaps

Validation data (provide some kind of incentives for utilities to provide the right kind of data

Operators experience with storage explicitly

Reliability/improvements experience system wide


Volume of data (reduce risk of basing decisions on wrong data)

System wide data

Development of models/policy based on early/new technologies like storage can be misleading

Level of Effort Greater than 10,000 person-hours

Key Features to Make the Analysis Used and Useful to Policy and Decision

Makers

Illustrate the benefits clearly in comparison with other technologies, including cost-efficiency and carbon impacts

Clearly articulate message to the audience

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Power System Requirements To meet electric systems requirements, it is important to understand how storage can be integrated into

long-term planning and how storage can displace the competing alternatives in the planning process. To

do this effectively, there needs to be a tool that can model and quantify the impacts of storage, as well as its

value. The results will depend on the scenario chosen and the valuation methodologies used. One way to

proceed is to ensure an accurate module can be used with existing tools (power flow, dispatch, and

economics, etc.), or, if not, a new tool may be needed. This links directly to the issue of how best to operate

storage to maximize the value and to capture all the benefits, in particular, reliability, while avoiding

perceived benefits that may not materialize. Ultimately, the tool should be able to perform contingency

analyses, provide a standard representation of storage types, and be capable of testing alternative dispatch

algorithms and assumptions. Since multiple benefits of storage have been recognized, it would be useful to

understand the value of each benefit individually and how 2 or 3 benefits combine together optimally. Data

will be needed to validate these tools or modules and current demonstration projects should be leveraged.

Another aspect to understand is the role and impact that distributed storage has on bulk power markets. A

tool should be able to help determine the optimal size and location in several scenarios for decision makers

and planners.

Electricity Markets Existing market structures are proxies for competitive markets, and participation spans the spectrum from

regulated entities subject to the traditional ratemaking process to deregulated entities bidding into organized

wholesale markets run by the regional transmission operators. The economic viability of energy storage may

depend on its ability to recover capital costs through multiple value streams, and full revenue recovery may

not be possible even if there is a potential societal benefit. In the current structures, the lack of revenue

POWER SYSTEM REQUIREMENTS, Part 2 Analysis/Research

Question How to maximize the benefits of distributed storage in bulk power markets?

Optimal size/optimal location – electrical, physical

Quantify the value of each benefit

Determine 2-3 optimal sub-sets at each deployment and account for appropriate revenue streams


Tools

Economic analysis

Reliability analysis

Societal and environmental analysis

Data Needs and Gaps

Data from users

System data


May not have identified all of the applicable benefits

Need better cost analysis

Need data from multiple sources/storage types

Perceived benefits that don’t materialize

Level of Effort Significant amount of time to collect data


Makers

The tool that analyzes several scenarios and clearly reflects the optimal sub-set will be crucial for decision makers

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recovery may result from various issues; some grid services are not monetized, grid product definitions have

technology biases, or system operations do not perform necessary co-optimizations. Additionally, most

current structures do not allow revenue recovery simultaneously as a regulated asset and as a participant in

wholesale markets. Therefore, even if revenue recovery is possible for individual value streams, only a

subset may be realizable for a single installation.

There is a need to look at the underlying demand and supply for grid services and identify system needs,

including what sources are providing those services and who else could enter a market for those

services. To justify new market structures, the analysis should demonstrate a substantial consumer or

producer surplus to be captured, understanding that in designing new market structures, there is a

trade-off between optimization and transaction costs. Optimal commitment and dispatch of storage

may require managing the state-of-charge based on projections of future prices. The time horizon

increases with the hours of energy storage, on the order of the dispatch schedule interval for energy-

limited devices and on the order of days for large bulk storage technologies like pumped hydropower or

compressed air systems. New market structures can be built into unit commitment/dispatch models

with examination of shadow prices or can be based on engineering assessments of power system

requirements with a supply curve for each service.

ELECTRICITY MARKETS Analysis/Research

Question What market structures are needed to support the energy storage business case?

How do you lower grid capital and operating costs (or delivered cost of energy) without preference to any resource?


Tools

Voltage support

Regulation

Primary frequency response (0-4 seconds)

Voltage stability

Transient stability

Small signal stability

Remedial action schemes

Black start

Non-spinning reserve

Capital deferment

Capacity

Data Needs and Gaps

Planning models (e.g., NERC ERAG, MMWG, PSS/E, PSLF)

Dynamic PSLF model

Generation schedules, forecasts of load, wind, solar, etc., load data, interchange data

Correlation of renewable integration, regulation requirements

High speed frequency

Supply curves (gap?)


Lack of understanding

Regional evolution of markets

Path dependent (sequencing)

Stakeholder engagement/regulatory risks

Software tool development risks

Risk of not needing a market due to policy changes(obsolescence of market design)

Level of Effort Investigating one regional market proof-of-concept – 2,000 to 3,000 person-hours


Makers

Increase the consumer and producer surpluses

Load transaction costs

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VALUATION METHODS, Part 1 Analysis/Research

Question Recognizing that distributed storage can be committed to multiple applications, are there tools to help find the total value of “combined” applications for the next 10 years for both distributed and bulk system applications for both distributed and bulk system applications?

This would be a forward looking tool for decision making


and Tools

Need to determine the individual value of each application using enhanced production cost and capacity expansion models, distribution systems modeling, power flow, etc. – different applications may need different methods.

Need to quantify the compatibility between different applications. This is done for market applications, but needs to be expanded to all applications of energy storage, e.g. compatibility between distributed application for supporting distributed PV and same storage in a market.

Need to optimize for maximum total value – will be different in different systems.

Data Needs and Gaps

Required data is generally available and can be obtained


The uncertainty resulting from forecasting future scenarios from past data sets is likely to be greater than the uncertainty from the methodology itself.

Level of Effort 10,000 person-hours


Makers

User friendly

Transparency of modeling assumptions

Apply simple stochastic approaches (sensitivity analysis to input data)

VALUATION METHODS, Part 2 Analysis/Research

Question What is the capacity credit to give storage for resource adequacy?


and Tools

Apply established ELCC and LOLP methods to storage, but modified to consider storage dispatch

Evaluate how storage fits into existing capacity markets

Data Needs and Gaps

Use standard datasets used for typical LOLP analysis

Evaluate storage dispatch strategies that can account for low-probability but high cost/value reliability events such as stochastic dynamic programming


--

Level of Effort Less than 2,000 person-hours


Makers

Examine how capacity credit changes as a function of the size of the storage reservoir (i.e. is the capacity credit of 15-min of storage different than the capacity credit of 2 hours, 6 hours, or 12 hours of storage?)

Account for uncertainty in the timing and duration of reliability events for determining the contribution of an energy-limited resource to adequacy.

Valuation Methods Algorithms and methodologies are needed to assess the value of a combination of location-specific,

compatible revenue streams over the future lifetime of a storage asset so investment decisions at

present can be made. The value of individual applications/revenue streams should be calculated using

production cost and capacity expansion models as well as other suitable models for different

applications. The compatibility assessment and optimization between different applications has been

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partially conducted for production cost related applications, but must be extended to all uses of storage,

so that different applications can be looked at in parallel without double counting. Existing data is

available to quantify the value streams at present in some situations, but using these to forecast what

the application values will be in the future is a significant source of uncertainty. It is critical that the

presentation of results be user friendly and accessible to decision makers. The value of distributed

storage to the bulk power system can be incorporated into this effort.

The appropriate capacity credit given to storage for resource adequacy can be determined by applying

established effective load carrying capacity (ELCC) and loss of load probability (LOLP) methods, modified

to consider the detailed operation of storage, which can be non-trivial. A related area for investigation

would be to evaluate how storage fits into existing capacity markets and what changes can be made,

such as having more granular time resolution, that would enable the system value of storage to better

represented.

ECONOMICS

Analysis/Research

Question

What is the value of energy storage as a function of cost?

Incumbents:

What applications? Include separate applications and quantify separately

Identify incumbents

Cost, performance, sensitivities for the incumbents…cost (net present value)

Market size:

Present market size by application

Resize different markets by scenario (e.g. how does regulation market size change in scenarios with high RE?)

Preferred

Methodologies and

Tools

Economic analysis of each…quick pass top identify “best” and “niche”, focus on

“best” applications.

Literature to develop baselines and summarize past studies and obtain past databases and update

Establish market sizes and relationships/functions between scenarios and markets

Obtain relationship between market size and performance of storage (does

regulation market size shrink w/ fast response storage?)

Data Needs and

Gaps

Accurate cost/performance curves for existing technologies

Collect cost/performance for U.S. ARRA storage projects and establish value story

Biggest data challenge: Identify number of lines, transformers, and candidates for

storage involving deferral of T&D infrastructure.

Need to interview utilities and establish relationships

Risks, Limitations,

and Caveats

Accurate incumbent technology cost curves

Accurate scenarios of macroeconomics and markets

Level of Effort 5,000 person-hours

Establish ~10 member Technical Review Committee that knows the incumbent technologies and markets

Review study quarterly

Key Features to

Make the Analysis

Used and Useful to

Policy and Decision

Makers

Select relevant policies and regulations for each scenario

Strike a balance between depth/thoroughness, and broadness and focus on big

markets rather than niche markets

Clearly identify gaps and the importance of the gaps

Highlight trigger points needed for storage to grow rapidly

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Economics It is important to understand the economics of storage, namely the size of the storage market as a

function of storage cost and capabilities. Improved understanding of the “cost-curves” for storage can

help in giving more clarity to investment decisions in terms of high value applications and large market

segments. There are published reports of “cost-curves” for storage, but they are only applicable for a

particular set of assumptions. A framework that can be applied for a wide range of scenarios is

desirable.

One potential framework that can be used is to characterize and quantify the different applications and

services where storage can be used. The first step would be to identify the incumbent technologies that

currently provide the identified grid services and to understand the costs, performance, and sensitivities

associated with those incumbents. Next, it will be necessary to identify the market size for the various

applications and gain an understanding of how those market sizes will change according to the scenario. A

quick pass can identify the “best” and “niche” applications for storage, and a literature search can provide

a baseline for these applications. It is important to keep in mind how the market size for an application

may change depending on the performance/characteristics of storage.

A simple and transparent analysis framework is necessary for stakeholder buy-in. A well-developed

framework can then be used to identify the value that storage can provide, setting the target cost

needed for storage to become economical. There will be local differences in markets and values for

applications and services, and these differences also need to be kept in mind.

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Appendix

Participants

Invited Experts Audun Botterud ANL Paul Denholm NREL Ross Guttromson SNL Gerald Heydt ASU, PSERC Michael Kintner-Meyer PNNL Rao Konidena MISO Soorya Kuloor GRIDiant Corporation Devon Manz GE Ralph Masiello KEMA, DOE EAC Andrew Mills LBNL Ali Nouri KEMA Emeka Okafor AEP Mark O’Malley UCD Arnie Quinn FERC Brad Roberts S&C Electric Company, DOE EAC Aidan Tuohy EPRI

Department of Energy Observers Paul Bakke EERE, Golden Field Office Sam Baldwin EERE Mike Davis EERE Rajesh Dham EERE, Water Program Pat Hoffman OE Philippe Larochelle ORISE, ARPA-e

Planning Team Kerry Cheung AAAS, OE Carla Frisch EERE Imre Gyuk OE Ookie Ma EERE Ciara O’Dwyer (Note taker) University College Dublin Bill Parks OE Rich Scheer (Facilitator) Scheer Ventures

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Initial Questions The following questions were posed to the workshop participants ahead of the workshop and were

designed to stimulate thinking.

1. Valuing storage is a multi-dimensional problem. Are there ways to come up with simple parameterizations that capture the costs and benefits based on system characteristics and location?

a. How important is detailed modelling in valuing storage? b. Do we need high time resolution (seconds or less) detailed models (e.g., explicitly model

fast response like regulation services)? c. How important is detailed modeling of the network topology in valuing storage e.g.,

storage may have localized benefits due to congestion patterns)? d. Do we need multi-scale models that are coordinated (i.e., hourly to five minutes to

seconds and/or EHV to distribution)? If yes, how integrated/coordinated should the effort be in terms of temporal and spatial scales?

2. Should we use a market/price-based approach in valuing storage, OR should we look at a cost-

based approach (e.g., storage should depress price spreads, killing its own market, but may still provide value to the system from a cost perspective)?

a. Should we use historical or simulated market price data to value storage?

3. Should we model long-term evolution issues? How far forward should we consider( i.e., today, 5 years, or 10 years or more)?

4. How should we model storage providing ancillary services, especially those that are not

currently market-based (e.g., there is no market for inertial response or frequency response, so valuing them is difficult)?

5. What are the critical modelling issues in valuing multiple value streams for storage (e.g., storage

can provide energy arbitrage opportunities and contingency reserves and get paid for both – but how can we model this accurately as they occur at such different time scales)? Also, from a reliability perspective, getting multiple services from any one source is prone to possible double counting.

6. What storage scenarios are most important to examine?

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Group Discussion Template

ANALYSIS AREA

Analysis/Research Question


and Tools

Data Needs and Gaps


Level of Effort

Key Features to Make the Analysis Used and Useful

to Policy and Decision Makers

analytic challenges to valuing energy storage · sixteen stakeholders and experts from across the...

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